“The Ju/’hoansi people of the Kalahari have always been fiercely egalitarian. They hate inequality or showing off, and shun formal leadership institutions. It’s what made them part of the most successful, sustainable civilisation in human history…” James Suzman in The Guardian, October 2017
“Open scientists in the academy are fiercely egalitarian. They hate inequality or showing off, and shun formal leadership institutions. It’s what made them part of the most successful, sustainable intellectual forces in human history…” Hopeful message from the near future.
Why fierce equality matters to the academy
The academy needs equality, and not just the word. It needs normative, active, celebrated, fierce equality. It needs this first as a corrective to the twisted incentives of the past century of perversely cumulative advantage (DiPrete and Eirich 2006). It needs this as an open door for scientists in the south who have been locked out of conversations. It needs this to ground a new operating logic that does not permit the hiring of temporary faculty at penurious wage scales. It needs this to repair so many years of gender inequality. It needs this because the best science comes from a requisite variety of knowing that is all inclusive. Here we will explore this need.
The contrast between what fierce equality would look like in the academy and what you will find today, looking around your university, your discipline, your career (and those of your students), is probably striking. It was never supposed to be this way.
Science was meant to be rigorously inclusive. Merton (1942) used the term “universalism” to describe the foundational democratic norm of science (one of four norms, also the norm that most tended to be “deviously affirmed in theory and suppressed in practice” (ibid)). Universalism meant, and still means, that scientific discoveries can be made anywhere, by anyone. New discoveries are validated by the community (usually through replication). Their discoverers have equal standing in the “republic of science”(Polanyi 1962) without the need for additional institutional or personal validation. There are pragmatic constraints about proper methods and reporting that add a higher threshold to enter the cadre able to do and report science. Fierce equality ensures that crossing this threshold is not anybody’s exclusive privilege.
The suppression of universalism has several sources, including the external logic of neoliberal markets. Another factor is what Merton termed the Matthew effect. The Matthew effect describes all the ways that advantages accrue to a few individuals and are, simultaneously stripped from the rest. “Differences in individual capabilities aside, then, processes of cumulative advantage and disadvantage accentuate inequalities in science and learning: inequalities of peer recognition, inequalities of access to resources, and inequalities of scientific productivity. Individual self-selection and institutional social selection interact to affect successive probabilities of being variously located in the opportunity structure of science” (Merton 1988).
Cumulative advantage has well-studied institutional and geographic features, which lead to advantages and disadvantages in hiring, funding, and publication. Despite a raft of entitled pronouncements to this effect, the academy is not a meritocracy; or else, it’s a terrible example of one (Morton 2019 (Accessed May 30, 2019); Standing 2011; Emkhe 2018 (Accessed May 30, 2019); Way, et al. 2019; Harmon 2018 (paywalled, Accessed May 30, 2019); NAS Committee on the Impacts of Sexual Harassment in Academia 2018). Academia is an informally reproduced aristocracy. It was never supposed to be this way; apart from the fact that it’s been this way for a long time. Which is why fierce equality matters.
“It is the priority rule which identifies the author of the discovery as soon as he or she publishes and which thus determines the constitution of “reputation capital,” a decisive element when it comes to obtaining grants. ‘The norm of openness is incentive-compatible with a collegiate reputational reward system based upon accepted claims to priority’ (David 1998). The priority rule creates contexts of races (or tournaments), while ensuring that results are disclosed. It is a remarkable device since it allows for the creation of private assets, a form of intellectual property, resulting from the very act of foregoing exclusive ownership of the knowledge concerned. Here the need to be identified and recognized as the one who discovered forces people to release new knowledge quickly and completely. In this sense, the priority rule is a highly effective device that offers non-market incentives to the production of public goods…” (Foray 2004).
Hyper-competitiveness at the institutional and personal level “crowds out” (Binswanger 2014) science’s intrinsic motivations and promotes quantity over quality, “bad science” (Smaldino and McElreath 2016), and marketable formalism over research needs. Worse, it crowds out scientists who refuse to play the bullshit-excellence game required by the gamification of reputation in the academy. The “priority rule” of discovery in the academy is really just a method to gamify episodes in the lives of research teams for the reward of individuals against the benefits of discovery for science and the world. Foray does not claim that personal recognition is required for scientists to rapidly release research results; or that personal ownership of the knowledge contributes to knowledge sharing. “On the contrary, the tournament contexts created by the priority rule, as well as the size of related rewards, tend to encourage bad conduct” (ibid). The production of the public goods of science in these circumstances has become sub-optimal, feeding the goods of reputation metrics instead of the benefits of open demand sharing across the academy.
Competition also feeds the Matthew effect: “[I]ntense competition also leads to ‘the Matthew effect’…this competition and these rewards reduce creativity; encourage gamesmanship (and concomitant defensive conservatism on the part of review panels) in granting competitions; create a bias towards ostensibly novel (though largely non-disruptive), positive, and even inflated results on the part of authors and editors; and they discourage the pursuit and publication of replication studies, even when these call into serious question important results in the field” (Moore, et al. 2017). Science loses on all scores.
For science, hyper-competitiveness is a race to the bottom that so many institutions are fighting to win using arbitrary metrics as goals. “Competitiveness has therefore become a priority for universities and their main goal is to perform as highly as possible in measurable indicators which play an important role in these artificially staged competitions” (Binswanger 2014).
Universities, funding agencies, and major foundations will need to construct new hiring, promotion, and funding practices that ignore ersatz excellence, pseudo-merit, and cumulative advantages. This process begins by envisioning how the outcomes of funding can be shared with equity across society, and then operationalize this vision. A recent funding model (Pluchino et al. 2018) revealed that, since talent is well distributed across research populations, funding researchers who have already had a success (mainly due to luck, which is another interesting finding) underfunds others with great talent, but less fortune to date. Giving every researcher access to some funding would result in greatly improved research returns on these funds. Refactoring hiring, promotion, and funding is the academy’s greatest need, and largest challenge, today. Changing the core logic for hiring, promotion, and funding will be a monumental task (Smaldino, et al. 2019). Failing this task, science will continue its race to the bottom. Tossing this task onto the shoulders of “open science” is perhaps unfair: this is a wider, deeper need of science and society (Newfield 2016).
What fierce equality adds here is a new/old logic to anchor the discussions and decisions over what must come next. Like Merton, you can begin with the classic science norm of universalism; this time around, it’s vigorously affirmed in practice. You will find discussions on alternative research funding schemes and tenure solutions in other parts of the Handbook. As we learned in The Work of Culture (above), the academy will need to change behaviors to change attitudes, to change practices, to change research culture toward new ways (and sources and, hopefully, new amounts) of funding.
What is “fierce equality” and how is this better than simple “equality”? You might note here that the Ju/’hoansi people, those hunter-gatherers who have practiced this for millennia, do not call their own cultural practices “fierce equality.” This is how anthropologists have captured the integral role that equality has in their cultural practices, and the tough behaviors that are used to maintain this equality. Highly visible, shared cultural behaviors protect this norm against those within their group who are “bad actors.” Fierce equality is equality publicly defended at every opportunity where personal or group entitlement pops up. Those who might argue that fierce equality would only work in small-scale cultural groups might want to reflect that most academic work happens in small-scale cultural groups (labs, departments, college faculties, teams).
“The more widely the republic of science extends over the globe, the more numerous become its members in each country and the greater the material resources at its command, the more clearly emerges the need for a strong and effective scientific authority to reign over this republic. When we reject today the interference of political or religious authorities with the pursuit of science, we must do this in the name of the established scientific authority which safeguards the pursuit of science” (Polanyi 1962).
Fierce equality means that open-science organizational behaviors: governance policies, rules, codes of conduct, plans for sharing and access to resources and to recognition, funding strategies, hiring practices, and face-to-face interactions are liable to be judged by how they promote equality within the global “republic of science.” Fierce equality operates internally in the academy (nobody expects the rest of the world to comply), and internally in all of the academy’s various organizations, each of which expresses this norm in their own self-determined governance. Every chapter in this book will talk about how open scientists can promote and perform fierce equality in their daily work.
Fierce equality challenges hierarchy in the academy. Benkler (2016/17; Accessed June 6, 2019) calls out hierarchy as a key concern when refactoring an organization: “The first is the concern with the power of hierarchy; the power within an organization to be controlling. This is the concern with the bossless organization, this is the concern with participatory governance.” The NAS (2018) pointed to hierarchy as a factor in “mistreatment” in the academy. Organizational change in the academy needs to start with unchallenged hierarchies.
Fierce equality is not a luxury. It is a long-term optimization strategy for the global republic of science; an expectation that emergent capabilities for sharing, mining, mixing, and reusing science objects can only realize their potential as a planet-wide, provident scientific resource when the entire community adheres (in multifarious ways) to the norm of equality. To build knowledge-maintenance organizations that are self-sustaining across decades and centuries of time, and for the whole of the global academy, there is no more fundamental principle than fierce equality. And there is no better time than now to refactor the academy using fierce equality as a foundational principle. Fierce quality was the advanced cultural practice system that informed the behavior of a majority of humans for tens-of-thousands of years.
“This research also revealed that the Ju/’hoansi were able to make a good living from a sparse environment because they cared little for private property and, above all, were ‘fiercely egalitarian’, as Lee put it. It showed that the Ju/’hoansi had no formalised leadership institutions, no formal hierarchies; men and women enjoyed equal decision-making powers; children played largely noncompetitive games in mixed age groups; and the elderly, while treated with great affection, were not afforded any special status or privileges. This research also demonstrated how the Ju/’hoansi’s ‘fierce egalitarianism’ underwrote their affluence. For it was their egalitarianism that ensured that no-one bothered accumulating wealth and simultaneously enabled limited resources to flow organically through communities, helping to ensure that even in times of episodic scarcity everyone got more or less enough.
There is no question that this dynamic was very effective. If a society is judged by its endurance over time, then this was almost certainly the most successful society in human history—and by a considerable margin. New genomic analyses suggest that the Ju/’hoansi and their ancestors lived continuously in southern Africa from soon after modern H sapiens settled there, most likely around 200,000 years ago. Recent archaeological finds across southern Africa also indicate that key elements of the Ju/’hoansi’s material culture extend back at least 70,000 years and possibly long before. As importantly, genome mutation-rate analyses suggest that the broader population group from which the Ju/’hoansi descended, the Khoisan, were not only the largest population of H sapiens, but also did not suffer population declines to the same extent as other populations over the past 100,000 years.
Taken in tandem with the fact that other well-documented hunting and gathering societies, from the Mbendjele BaYaka of Congo to the Agta in the Philippines (whose most recent common ancestor with the Ju/’hoansi was around 150,000 years ago), were similarly egalitarian, this suggests that the Ju/’hoansi’s direct ancestors were almost certainly ‘fiercely egalitarian’ too” Suzman (Accessed June 6, 2020).
Fierce equality opens up contributions from across the world of science, and works at strengthening the “long tail” of discovery where real diversity spawns a massive variety of intelligences and promises innovation, discovery, fresh ideas, new knowledge. Fierce equality upholds the academy as an open gift economy, with its own logic of demand supply.
As Lewis Hyde puts it: “A scientist may conduct his research in solitude, but he cannot do it in isolation. The ends of science require coordination. Each individual’s work must ‘fit,’ and the synthetic nature of gift exchange makes it an appropriate medium for this integration; it is not just people that must be brought together but the ideas themselves” (Hyde 2009). You can check out Gifting and Reciprocity later in the Handbook. What is important here is that “the academy” or “the republic of science”—whatever you wish to call the planetary endeavor for new knowing—needs to operate as a specific type of gift economy, using Demand Sharing as its logic, and fierce equality as a core norm. An interesting tension that Hyde notes and resolves is how the academy uses knowledge (e.g., published papers) as gifts to offer status rewards, but does not actually attach this status to individuals as much as to the quality of their work and to their willingness to give this away to the scientific community. Any additional “prestige” attached to these gifts actually works against the interest of the global science community, and can be labeled a perverse effect on this.
“If you can find it within yourself to stop using conversations as a way to convince people that you’re right, you will be stunned at what you’ve been missing. A flood of information will rush in to fill the vacancy left behind by your ego. You might be overwhelmed with knowledge, perspective, insight, and experience. You’ll hear stories you had refused to hear because you were too busy stating and restating your case. If you enter every conversation assuming you have something to learn, you will never be disappointed.
If you want to articulate your opinion, write a blog. If you want to have a conversation, set your opinions aside, at least temporarily. You might find you never want to return to them. You may find you’ve evolved beyond them” (Headlee 2018).
Fierce equality is about equity of inclusion in academic life and work. It makes no claim about the relative qualities of the ideas introduced into the scientific conversation. All ideas are liable to validation and evaluations of their usefulness within their research domains. All findings are liable to interrogations of the methods and data that produced them. All scientists deserve to be heard, to be an equal part of the conversation.
Fierce equality is about erasing the dead weight of privilege, in exchange for open (as in to all, with additional recognition for contributions) knowledge collectives: cultural groups inside, outside (or both) of the current academic establishment. The goods of the academy will still be vetted; in fact, reviewed with greater transparency, fairness, and effectiveness than current peer review (Tennant, et al. 2016).
“Given the right opportunities, humans will start behaving in new ways. We will also stop behaving in annoying old ways, even if we’ve always tolerated those annoying behaviors in the past” (Shirky 2010).
Applying a logic of fierce equality to your organization might present a variety of challenges. Your long-standing academic organization may have settled into any number of “annoying behaviors” that are defended as traditions, or simply as “the way we’ve always done things.” This Handbook is here to help you become a culture change agent, to kickstart the conversations that decenter pre-internet, pre-open science practices. Open science is here to offer a whole mix of “the right opportunities,” so your organization can do better things and stop getting better at doing obsolete things (Dintersmith 2018).
A vision of the academic world operating though fierce equality is a thought experiment that many people in many academic organizations will need to do in the next decade. You and your colleagues can open up Culture Changing Activities beginning with statements about values and vision.
Here is one example of a fiercely equal, future-of-the-academy vision statement:
We envision an academy where members openly share their most important thoughts, processes, data, and findings through self-governing commons that are intent on the long-term stewardship of resources, on the value of reuse, on the absolute equality of participation, on the freedom of scientific knowledge, on open access to common infrastructures, and the right of all to participate in discovery and of each to have their work acknowledged, if not with praise, but with kindness and full consideration.
The particulars that inform this vision might include the following:
Widespread use of lotteries for institutional or volunteer “leadership” positions (including department chairs and some deans), with initial terms of office fairly short (just long enough to evaluate performance) and opportunities for follow-on appointments (with limits). Good service is still noted and can be another source of informal recognition.
Badges—when these are openly available to be acquired— can also be used as preconditions for entering lotteries. Want to be considered for dean? Take this badge MOOC. Skilling can be acknowledged and rewarded through badges. Badging also can become a primary task for professional associations/societies, as long as the ability to acquire the badge is not made exclusive.
The act of making one’s science work objects publicly available supports non-exclusive, anti-scarcity services: open repositories, pre-prints, idea farming sites, etc.
Career moments (promotion, job switching, etc.) are evaluated externally, and keyed to a record of active demand sharing, indications of non-assholish behaviors, and activities that celebrate the institutional values and norms. Also, job applications have a layer of lottery to randomize selection (perhaps between an initial evaluation and the final decision). Implementing this is tricky and will require experimentation to optimize.
Lotteries are distributed into diversity buckets to be sure that the variety of selectees includes those who might otherwise be excluded.
Funding gets spread out to the long-tail of the community, with an ability to/requirement to also crowd-source the redistribution of some funds to promote work that is of widespread benefit.
Laughing at bullshit “excellence” and at the former desire to build exclusive academic “brands.” Remember it is possible to be elite, without being exclusive. Remember “Harvard”? Remember “Nature”? Smile. Recognition shifts away from individuals and institutions and to the actual work and all the teams currently adding to this, and the long history of that work.
Nobel—and other—prizes honor ideas shared among networks (Keating 2018). Lists of scientists across the planet who have contributed to a selected avenue of research might be assembled, mainly as a reference for future collaborations or historical records. Even as we might ridicule a government official for demanding gratitude when he was only doing his job, we need to start ridiculing those who want to claim personal credit for research results that a built on a wellspring of shared knowledge, teamwork, and luck.
“If I have seen further it is by standing on the sholders [sic] of Giants.” Isaac Newton. 1676. Letter to Robert Hooke (before they became bitter enemies). This notion was a commonplace in the 17th Century, with the implications that even a dwarf would see further than a giant if he were standing on the giant’s shoulders. (Wikipedia).
“If our team’s ideas add value to the current state of knowledge, it is because we have stolen widely and well from the abundance of prior understanding surrounding us, and climbed a stairway of knowledge built by others.” Modern version… no giants.
It’s time for science to admit that no scientist is a lone giant in their field
One of the hard lessons for open science is to abandon the notion that “great” scientists—those “giants” of the academy—were and are individuals of some unique and rare quality; that their shoulders tower above those of their peers, and that the optimal career goal of a scientist is to become a giant in their field. And, if you are a woman in science, while standing on the shoulders of “giants” in the academy, you can be fairly certain that some of them would have been intent on looking up your skirt; another reason why open science needs Fierce Equality.
In Isaac Newton, the Asshole who Reinvented the Universe (Freistetter 2018) we get a picture of Newton’s brilliance as a natural philosopher, and of his serial acts of intellectual and careerist selfishness. Biographies of Newton’s career and personality issues are several (See also: Clark and Clark 2001; Manuel 1979; Gleick 2004). The biographies of several of his contemporaries (Leibniz, Hooke, Gray, and Flamsteed for starters) reveal their side of the dangers of being on Newton’s wrong side. But then Newton’s bad behavior was not as unusual as it perhaps should have been. Rather, it was distinguished by its obsessive persistence, and made potent by Newton’s position at the head of the Royal Society. Freistetter excused much of Newton’s bad behavior as emblematic of an academy culture where intellection was—and still is—a cerebral variety of blood sport. He did venture that Newton would still be called an asshole if he were working today.
Newton’s interpersonal misconduct is less of an issue here. For more on assholes, take a look at The Zero-Asshole Zone. While producing a series of astonishing research findings from his own work, Newton was soaking up ideas and credit from others, while insisting that his ideas were his alone. Apparently, we wasn’t entirely serious about the whole “giant sholders” thing.
You want to get good at doing science—as a personal goal—because this leads to more satisfaction in your daily life and career, and because you can become more valuable to science by having better conversations that lead to more interesting questions and new ideas. You getting better at being a scientist should, in no manner, obstruct others on their path to getting better at this. In fact, one of the advantages of open work in science is that you can lift others during your climb up the same stairs. You can always grow. You can grow a larger sense of the science you are working with/on, a perception of how your work fits into the field, and appreciation for the work of your colleagues. Your primary challenge is to be better at science (and being human) today than you were yesterday.
“[B]y some measure, every important innovation is fundamentally a network affair” (Johnson 2011).
“[M]odern scholarship is based on cooperation. Ideas are not created in a vacuum. Reuse of research processes, methods and results as well as abstraction and extension should therefore represent basic values of scholarly communication. The possibility to reuse data, materials and results enables researchers and communities to learn from each other and to speed up the production of new knowledge” (Vienna Principles 2016; Accessed July 10, 2020).
What’s wrong with having and celebrating “giants” in your field? We can explore this. Firstly, the goal of exclusive achievement and individual fame requires and produces way too much scarcity in the process. In the game of “giant-making,”recognition points might need to be hoarded, reputation metrics jealously guarded, and ideas (and data) locked away until some strategic moment. Secondly, the practice of acknowledging a science giant requires the production of science dwarves. It’s a zero-sum game. If nobody is small, someone can’t be giant. Most giants only look large from far away because of the cumulative advantages they were given across their careers. They are standing on the shoulders of privilege. Finally, the desire to be a giant fuels narcissistic behavior, which the academy has an abundance of already.
“As Justice Louis Brandeis, who witnessed our previous Gilded Age, might have said: ‘We may have democracy, or we may have praise showered on the heads of a few, but we can’t have both’” (Johnson 2019: Accessed July 24, 2020)
In a fiercely-equal, open-science culture, zero-sum games of prizes and awards handed out to would-be giants can be replaced in favor of a larger emphasis on a system of open badges that anyone can earn: with intention, time, and effort. The use of badges earned instead of prizes won for recognition of accomplishments would build a reputation economy for the academy that rewards achievement anywhere on the planet, and refocusses attention on science’s generative engine: learning and community effort. “Although the edifice of scientific understanding is sometimes envisaged as an accumulation of individual discoveries, in reality science is a community effort comprising innumerable interdependent contributions. Credit is disproportionately awarded to principal investigators for what is truly the product of teamwork, and nearly all scientific contributions are heavily dependent on knowledge obtained earlier…. In the spirit of an Amish barn-raising, a celebration of the collective achievement of science should subsume individual achievement” (Casadevall and Fang 2012 [ASM]).
The finite game of “making a name for oneself” in the academy is far too expensive to the academy to allow this to be a central goal of science. Science demands so much already from you: both rigor and wonder, and in generous amounts. “Science is an inherent contradiction—systematic wonder—applied to the natural world” (Lewis et al. 2001).
Because it is important to regularly celebrate open science cultural practices, and contributions to science, and to institutions, and teams, you can create honors that are playful and honest. Science doesn’t need fellows in national academies as much as it needs researchers who can get honored for their dedication and their kindness. Be generous to those who are, too. Don’t tell your team members to “leave their frowns at home,” but hand out medals (perhaps made of chocolate) to those with the most difficulties to overcome, and the best spirit. Give away prizes every week. Cheer when someone earns a difficult badge. Turn learned society elections into lotteries, and celebrate when volunteer leaders chosen at random step up and perform. Find ways to reward as many early career colleagues as possible. In the end, you realize that everyone who makes a serious attempt to do science is already a giant. You didn’t notice because you are one too.
An elite cohort is a group of individuals where some special level of skilling makes these particular individuals eligible to join. An exclusive cohort is a group that has created a scarcity and manages entry. The group reserves the right to join. Private clubs can be really exclusive while not being regarded as elite (at least by others).
Free divers as a cohort can support an elite group among them without needing to consider restricting entry, without becoming exclusive. You want to be an elite free diver? Work at it. Dive deeper. Then dive even deeper. You can achieve elite status on your own.
The academy is already elite. Only about one percent of humans over the age of twenty-one have a PhD. Only a very small minority of people (with or without PhDs) decide to spend vast amounts of their time exploring unknowns in the universe. This means that the academy has no need to also be exclusive. Like bullshit claims for “excellence” (Moore et al. 2017), claims for exclusivity are counter-productive. They announce that science can only be accomplished by a selected few. Selected by whom? Editors at Elsevier?
Still, within the cohort of scientists, some are known as really good scientists. These elite scientists are self-selecting. They select how much work they plan to put into doing good science.
“A central claim made by proponents of open and collaborative production is …based on the argument that commons-based, non-proprietary systems of production are able to draw on a much wider range of human motivations than those deriving from participation in markets, or coercion by managerial command and waged labour. Benkler (2006) suggests that the freedom to co-operate in collaborative ways with others to make things of value to humans, and to be generous and kind (behaviors and patterns familiar to us from social relations generally) motivates people far more effectively and efficiently than traditional market mechanisms or hierarchical models of social organisation”(van Zwanenberg et al. 2017).
Open science will help you to do what you need to do to become an elite scientist: build your knowledge, your craft, and your reach. Share your research work flow so others can offer advice and kudos. Share because sharing accelerates the feedback that drives new ideas in your own work. Share because others will take your data to places you never considered.
Open science is the smart way to become elite. Be elite not through some erzatz “journal impact factor” but by sharing your work openly, and by being generous with your colleagues, particularly those few who are struggling with the same object of study you have chosen.
You and a handful of other scientists have somehow been drawn to the same problem, the same phenomenon. Together you can dive deeper into this problem than you can ever go alone. The only impact factor you need is the one that comes in your inbox from a colleague thanking you for solving one of their research pain points.
Afterthoughts: If you still want to be a giant, be a giant for your family, be a giant in your town. Perhaps there used to be giants, back when the only way to fund science was to attract the attention and the purse of a king. If the person paying your rent is named de’Medici, perhaps you should get used to wearing stilts, just ask Galileo Galilei. The main lesson of that famous “standing on the sholders of giants” quote is that if you are going to be a life-long jerk, pop some really nice sentiments on your blog that people might remember you by three hundred years later. Even then, someone will write a book about what an asshole you were.
In a famous letter of 1813, Thomas Jefferson compared the spread of ideas to the way people light one candle from another:
“He who receives an idea from me, receives instruction himself without lessening mine; as he who lites his taper at mine, receives light without darkening me.”
We’ve all heard about the “sharing economy,” where we can gain new streams of income or convenience by simply sharing excess capacity (that spare room, the car ride, an electric scooter, etc.). And we’ve been told since childhood that sharing things we no longer need can help those with greater needs. Most of us feel we have a good idea about what it means to “share.” But then most of us are also mistaken, and here’s why.
Anthropologists who look at the ethnographies (and who do their own) of hunter-gatherer groups, and who sometimes also look at modern attempts to create sharing economies (e.g., Uber, Airbnb, etc.), tell us several things about sharing that most of us may find new and different from what we expected (Widlok 2016; Suzman 2018; Accessed May 6, 2019). These ideas about sharing, synthesized from the study of human groups that have been successfully building their own lives for tens of thousands of years, say to us that we have “sharing” almost completely wrong.
Real sharing is not charity. Charity is an artifact of the marketplace (and of personal wealth) and the logics of artificial scarcity.
Sharing something you own that you are not using (like a spare room or space in your car) in exchange for cash is just another form of market transaction.
Giving away things that you don’t need or no longer want is not a good example of sharing. This is an edge case.
In this Handbook, we use the phrase “demand sharing” to designate a culturally advanced form of sharing, a type of cultural behavior that has been in widespread use of the majority of the human population for tens of thousands of years, and only recently eclipsed by marketplace logics in the past two to three hundred years. “Millions of years of evolution have designed us to live and think as community members. Within a mere two centuries we have become alienated individuals. Nothing testifies better to the awesome power of culture” (Harari 2014). Additional information about demand sharing is available elsewhere in the Handbook.
A rather good (perhaps unexpected) example of demand sharing in modern society is having your representative government demand a tax that everybody pays, which then, for example, supports your state’s public colleges and universities (and pays your salary). That’s right; taxation is how a society demands of itself those resources it needs to prosper (Widlok 2016).
Another example is sharing within a household, where family members can grab a snack from the refrigerator without much bother or need to justify or account for their choices. In the case of the academy, the “refrigerator” is the rapidly expanding corpus of digital research objects, and the family is fellow scientists who stock this with the outputs of their work, and who can then dive in and grab what they need for their own research. Note: this is a never-empty refrigerator, as these digital objects are not used up by their taking. Note again: they are anti-rivalrous: they gain value when they are shared. This is something every open scientist needs to remember.
“[L]earning is taken as much as given” (Godin 2019; Accessed May 6, 2019).
Teaching and learning already require demand sharing. As an open scientist you’ve probably taught in a variety of classroom situations. Your students asked questions to extend their learning. Your best students (bless them) outright demanded to be taught. They marched into libraries (buildings, or on-line) and demanded the resources they need. They came to your office hours and demanded answers to their quandaries.
This means that nearly every scientist is well versed on how to participate in a demand-sharing economy. First, the state demands that its citizens fund the university, supporting teachers and learning. Then the student shows up and demands to be taught. We all did this as students. It’s not obscure, it’s how we learn.
Imagine a professor giving a lecture who stops in the middle and says, “This next part is really interesting; if you want to learn it, go to my app on your phone and deposit $10.” This should sound bizarre to you: if it doesn’t, then the neo-liberal university is your real home. In part it sounds strange because the professor’s salary is already paid, hopefully through taxes. But mainly, it sounds wrong, as professors (who were once students) are completely happy for their students to learn. These learning moments in the classroom are seen as socially important and personally rewarding. When a student asks you a question, you do your best to help them learn something new. Note: making your students buy a textbook you authored, for a price that might equal the rent they pay in a month, should also sound strange.
In a hunter-gatherer culture, such as that of the Ju/’hoansi, when a child comes to your fire and demands a bit of meat from your catch, you give it to them. Like food at a hunter-gatherer fire, information in a university is something that can be demanded. Demand sharing in education is a type of cultural economy where the norms and rules—the times and places, the manner of asking, the desire to teach and the value of learning—are well-known, without being written down. Students know they cannot demand the answers to a quiz in advance. What is sometimes forgotten is the need for and role of kindness in these interactions.
This means that you already know how to do demand sharing. Let’s look how demand sharing differs with what we just described as poor examples of “sharing.”
You don’t give your classes as a form of charity (even though you may consider your own salary inadequate). You are a professional. Teaching is important. Your students have legitimate demands on your knowledge and your kindness. Passing on knowledge is why you teach.
You also don’t teach your students content that you find worthless to you or loan them books that you are no longer satisfied with, unless these books are instructive in other ways. You share what is really important to your professional life: the best knowledge you’ve acquired.
You expect students (at least, grad students) to demand from you what they need to learn and grow as scientists.
This is the proviso we mentioned above. The same demand-sharing logic that collects the taxes that pay your salary, and enables your students to learn, also enables the academy to manage its knowledge resources for the benefit of all scientists, and the planet through the internet. Until today, a scientist might legitimately point out the huge amount of process-friction that would overly complicate sharing her data or workflows. A lot of the work of open-science advocates in the last two decades has been focused on reducing that friction through web-based platforms and services. Much of the remaining friction is cultural; linked back to institutional practices that do not reward or actively punish open resource sharing.
In an open-science, demand-sharing academic culture, sharing as much of your research as early as possible is a virtue strong enough to be a norm. Share what matters most to you: your methods, your findings (even null fundings), and your data. Share your ideas openly too, not simply those ideas that you have no interest in pursuing and every interest in having someone else pursue. Share your knowing by listening and adding to the conversation.
Open science requires generosity with a simple promise: each scientist will get more than they give. That’s the bargain the academy makes with you when you join and actively participate in the open-science academic society; a bargain that today gets broken all too often. It is the promise of the trove of knowledge that the academy maintains in libraries and repositories. This bargain is bolstered by the network effects of academy organizations. Demand sharing optimizes this bargain across academic networks and clubs (Redaction 2016; Accessed June 1, 2019).
Sharing imbeds your work into the community of science as a gift, a form of offering that also signals your membership. Sharing includes reviewing and acknowledging the work of your peers (See also: Perils of peer review). The open-science community creates its internal authority through relentless self-critique.
This authority works through a special type of reciprocity and a level field of mutual status. As Polanyi (1962) noted, “[O]nce the novice has reached the grade of an independent scientist, there is no longer any superior above him. His submission to scientific opinion is entailed now in his joining a chain of mutual appreciations, within which he is called upon to bear his equal share of responsibility for the authority to which he submits.” This reciprocal authority of “mutual appreciations”, based on openly shared and critiqued knowledge is the basis for all applications of authority and leadership in an open-science academy.
The offerings you provide to the “republic of science” (Polanyi 1962) lend you the cultural capital to demand the resources you need for your work from the abundance of open-access resources, and the knowing of others in your field. These, in turn, offer up their research for your use. As Hyde (2009) notes, the “constant and long-term exchanges between many people may have no ultimate ‘economic’ benefit, but through them society emerges where there was none before”; your contributions help create the academy society.
Amplified by the internet’s global reach, these exchanges expand and accelerate the process of science. You share the most important ideas you have, even at the risk of being scooped, because getting the most important work done now—whether you do this or someone else does (and attributes you with the idea)—moves science forward. You share your research results, all of them, knowing you will be critiqued by your peers, as you will also critique theirs.
One more advantage of demand sharing is the occasion where you find a piece of information outside your close associations and intellectual domain, and you demand (ask) to gain more knowledge so that you can include this in your work. Demand sharing activates weak ties (Granovetter 1983), bridging between knowledge domains to spark innovation. “From the perspective of innovation, it’s even more important that the information arriving from one of those weak ties is coming from a different context” (Johnson 2011). Of course, you will also, on occasion, be asked to give out knowledge around your research, opening up weak ties with new potential collaborators.
“The self-image of humans who are embedded in sharing relations is not one of homo faber who creates his or her world out of nothing and without anyone else. Rather it is an image of what I have called homo sumens … who takes into use what is available through the company of others and that can be claimed from them” (Widlok 2016).
Demand sharing is a dense cultural practice, with its own behavioral expectations. When you share, you signal your desire to be included in the community. What you must learn, then, are the guidelines for demanding resources. “[T]he problem is not one of deciding what to give to whom but rather what to demand of whom. The onus is on the potential receiver to make his or her claim acceptable and the rules for appropriateness are not about acceptable giving but acceptable demanding” (Widlok, ibid; emphasis added).
The cultural shift to demand sharing will create a social basis for new science collectives, for “clubs” that share internally as though the club were a single, social organism. These formations are not entirely new. R&D Think-tanks have been funded for this purpose, and the NSF in the US spends a billion dollars a year funding academic workshops to assemble temporary collectives to solve common problems. “Club goods” are non-rivalrous inside the club, but not necessarily without shared costs (Hartley, et al. 2019). Science club goods have the additional property of being anti-rivalrous. Thomas and Brown (2011) describe these clubs as collectives, “Collectives are made up of people who generally share values and beliefs about the world and their place in it, who value participation over belonging, and who engage in a set of shared practices. Thus collectives are plural and multiple. They also both form and disappear regularly around different ideas, events, or moments.” Collectives enable collaboration across the internet, inform team-building and open up the situations for shared knowing.
The cultural practices of demand sharing will be emergent in the academy as open resources—including access to and discoverability of collaborators—become increasingly available in the next decade. This Handbook will help you to kickstart your own collectives, and forge demand-sharing cultural norms that suit your situation; see also Building new collectives.
“That ideas should freely spread from one to another over the globe, for the moral and mutual instruction of man, and improvement of his condition, seems to have been peculiarly and benevolently designed by nature, when she made them, like fire, expansible over all space, without lessening their density in any point, and like the air in which we breathe, move, and have our physical being, incapable of confinement or exclusive appropriation. Inventions then cannot, in nature, be a subject of property” Thomas Jefferson 1813 letter, quoted in (Boyle 2008).
Together with “fierce equality,” demand sharing as a cultural norm can help realize an actual sharing economy for the academy, separated from the arbitrary scarcity of the neo-liberal marketplace; a special type of gift economy grounded in mutual appreciation, rather than reciprocity. The demand sharing economy helps scientists grow networks that are far larger than those available through simple reciprocity (Grant 2013), and also far more emotionally satisfying (no need to keep track of each transaction). The particular practices of demand sharing will need to grow inside thousands of institutions across the globe.
A goal of this Handbook is to give you the resources you need to build demand-sharing logics inside your academy homes. You can be a demand-sharing change agent by sharing your research objects and your research questions and problems; by listening more and adding your knowledge when asked. Demand answers from others; learn together. It’s science, not alchemy. You are not alone.
Building a gift economy: the dance of open science culture
“I am not saying science is a community that treats ideas as contributions; I am saying it becomes one to the degree that ideas move as gifts” (Hyde 2009).
“The specificity of [demand] sharing… is rather that it also constitutes sharing in, granting access to the flows of objects, their intrinsic goods, and their intrinsic value” (Widlok 2013).”
“That is the fundamental nature of gifts: they move, and their value increases with their passage. The fields made a gift of berries to us and we made a gift of them to our father. The more something is shared, the greater its value becomes. This is hard to grasp for societies steeped in notions of private property, where others are, by definition, excluded from sharing” (Kimmerer 2013).
So, you will want to change the culture of your organization to enable “demand sharing” (See: Demand Sharing). This is something the Handbook encourages, and, after reading this section, you will understand why. The goal of this culture change is to build an internal economy for the scholarly resources you are now assembling. This economy will do two somewhat intertwined things: optimize the value of these resources and support their use through practices that respect and enable fierce equality across the global “republic of science” and beyond.
The argument here is that the current, scarcity-based market economy that has penetrated inside the academy does neither of these things well enough, and sometimes not at all. Instead, it promotes hyper-rivalrous games to capture funding and prestige, while it marginalizes and silences the long-tail of science talent across the globe. What the market economy does do really well is capture external motivations that appear to power efficient use. Instead, these motivations infest the academy with unavoidable conflicts of interest and perverse incentives.
This form of economy ends up externalizing much of the value of research goods. These become properties held outside of the academy—from which they were born; this happens today, every time you gift Elsevier or Wiley the copyright to your research article. While this arrangement frees the academy from investing in the repositories that could hold these goods internally, and in recognition schemes to highlight great work and show gratitude to science teams doing this work, the cost is significant and ongoing: the academy needs to pay over and over again to access its own resources.
Slow is smooth and smooth is fast: with enough culture you can go slow enough to accelerate science
“What peer producers are doing—for now mostly in the sphere of ‘immaterial’ production of knowledge, software, and design—is to create an abundance of easily reproduced information and actionable knowledge; that which cannot be directly translated into market value, because it is not at all scarce—on the contrary—it is over-abundant” (Bauwens 2012; Accessed 10/2018) .
The cultural practices that support demand sharing are not simple at all. Not nearly as simple as the market transactions we do every day. They require active, culturally coded, shared intentions. Think of them as a learned, shared cultural “choreography.” Every member of the group knows how to dance with the group. These practices are durable enough to have sustained hunter-gatherer groups across the planet for tens of thousands of years, sophisticated enough to enable entire small societies to manage almost all of their internal transactions, and logical and transparent enough so that children do learn and follow them. Peer-to-peer production uses these same cultural practices to build the infrastructure of the internet.
“Almost everyone [in the social sciences] continues to assume that in its fundamental nature, social life is based on the principle of reciprocity, and therefore that all human interaction can best be understood as a kind of exchange…
…Exchange is all about equivalence. It’s a back-and-forth process involving two sides in which each side gives as good as it gets” (Graeber 2011).
Let’s look closer at socio/anthropological notions of a “gift economy” and “reciprocity,” and more recent work in economic history and economic anthropology for new insights to the “sharing economy.” In anthropology, reciprocity is a topic that has launched a thousand dissertations, that has informed entire schools of theory and argument, and that has been the wellspring of anthropology’s connection to economics since Marcel Mauss’s book, The Gift, was published in French in 1925.
The Handbook assumes your goal here, or one of them, is to avoid needing to become an anthropologist in order to be a culture-change agent. Here are the basics of gift economies and reciprocity you might call upon without further study. Let’s start with the conclusion: demand-sharing is a form of reciprocity that requires active, intentional cultural practices to deliver an optimal return for the academy. Demand sharing is a practical/theoretical upgrade on the notion of the academy as a “gift economy.” It describes a relationship in practice between scientists and science, between scholars and the academy.
At its core this is a durable obligation to interact with others. So, this behavior is culturally coded. Inside the community, exchanges get made that motivate future exchanges. Importantly, these obligations are never designed to achieve a final closure. Reciprocity in life and in the academy is a feature of infinite play. Reciprocity colonizes your future by enrolling you in longitudinal practices of giving and getting. When your child finishes college, you do not present them with a bill for all of the expenses they cost you growing up. If you do, you are planning to never see them again.
Market transactions (and also theft) avoid this type of ongoing obligation. So does charity, mostly. When you sell your old car to a stranger for cash, you have every hope that you will never see them again. When a thief breaks into your office and takes a computer, you do not expect them to give you something back in the future. When you give some food to a homeless person on the street, you don’t expect to get something material back from them later on.
Reciprocity takes more work (cultural and emotional) to maintain than direct market exchanges. It takes a shared understanding of the implied obligations for reciprocity to succeed as an economic logic. For this reason, reciprocity works best inside a community. Transactions between different communities involve more rule-making, and less cultural coding. Considering the academy as a community, or a collection of like-minded communities, some form of reciprocity is an economic logic that fits very well, once the cultural practices for this become normative.
In some cases, the implied obligations of reciprocity can negatively color the relationships between individuals: “When favors come with strings attached or implied, the interaction can leave a bad taste, feeling more like a transaction than part of a meaningful relationship. Do you really care about helping me, or are you just trying to create quid pro quo so that you can ask for a favor?” (Grant 2013).
Reciprocity can be generalized or more specific, and both forms can be active in the same culture. “Generalised reciprocity is characterised by Marshall Sahlins as being marked by a weak obligation to reciprocate and an indifference to the time, quality or quantity of the return. It is typically the behaviour found between such closely related people as parents and children or siblings, where asking for things is widely acceptable…” (Peterson 1993). Generalized reciprocity brings in a key feature of demand-sharing: the right to ask for what you need. You can say that demand-sharing is a certain specific type of generalized reciprocity, highly coded to be efficient and sufficient across an entire group (not just a family). So, what about gift economies?
“Gifts in Burning Man culture are offered unconditionally. In the case of individuals who contribute to our community, such gifts are relatively easy to accept, and it is only common courtesy to recognize these givers and their contributions. …This is an application of the Principle of Radical Inclusion” (Harvey; Accessed June 17, 2020).
“These remarks on the scientific community are intended finally to illustrate the general point that a circulation of gifts can produce and maintain a coherent community, or, inversely, that the conversion of gifts to commodities can fragment or destroy such a group. To convert an idea into a commodity means, broadly speaking, to establish a boundary of some sort so that the idea cannot move from person to person without a toll or fee. Its benefit or usefulness must then be reckoned and paid for before it is allowed to cross the boundary” (Hyde 2009).
“‘The important lesson I learned from Adam [Rifkin, a Silicon Valley entrepreneur] is that you can be a genuinely kind-hearted person and still get ahead in the world’ [quoting Stephanie, a LinkedIn recruiter]. Every time Rifkin generously shares his expertise or connections, he’s investing in encouraging the people in his network to act like givers. When Rifkin does ask people for help, he’s usually asking for assistance in helping someone else. This increases the odds that the people in his vast network will seek to add value rather than trade value, opening the door for him and others to gain benefits from people they’ve never helped—or even met. By creating a norm of adding value, Rifkin transforms giving from a zero-sum loss to a win-win gain” (Grant 2013).
Gift economies span from indigenous peoples to science cohorts, with Burning Man in the mix, somewhere. Speaking of indigenous gifting, Kimmerer notes; “The essence of the gift is that it creates a set of relationships. The currency of a gift economy is, at its root, reciprocity. In Western thinking, private land is understood to be a ‘bundle of rights,’ whereas in a gift economy property has a ‘bundle of responsibilities’ attached” (Kimmerer 2013). A great way to dive into the academy gift economy is to read Lewis Hyde’s (2009) book, The gift: Creativity and the artist in the modern world. In his book, Give and Take, Grant (2013) explores giving as a socially valuable practice for 21st Century commerce. Both Hyde and Grant use gifting to illustrate the value of “openness.” For Hyde, openness produces scholarly objects that grow in value as they are shared without regard to direct compensation. For Grant, openness creates weak ties across vast networks where generosity is also generative for creativity and innovation.
A gift economy uses gifting as its primary, and/or its celebrated form of exchange. There are no purely gift economies; people create exchanges for complex reasons that might not fit in this description, even when they use gifting for most exchanges (Graeber 2001). At Burning Man, where you can find someone to gift you any recreational drug you might desire, you can always purchase coffee at Center Camp. Gift economies co-exist with other forms, such as market economies. Hyde (2009) calls this a “mixed” economy.
In a non-gift economy, gifts can still be reciprocal, even if the return gift is only an expected “thank you.” Families may send out holiday cards and keep careful track of the cards they receive in return. They trim their card list accordingly. Birthday gifts or dinner invitations to friends open up expectations of similar goods coming back. Edge cases are also available. Oprah Winfrey added to her fame by giving away cars (accessed 06/20/2020) on her television show. Philanthropy channels donations to a range of causes where the return is not a gift, but some resolution of a deficit or a wrong. In what way is gifting essential to the academy?
The idea here is simply to catch the central meaning of what a “gift” is within a scholarly community. Hyde points back to Warren Hagstrom’s work on The Scientific Community (1965): “Hagstrom writes that ‘in science, the acceptance by scientific journals of contributed manuscripts establishes the donor’s status as a scientist—indeed, status as a scientist can be achieved only by such gift-giving—and it assures him of prestige within the scientific community’” (Hyde 2009). However, this exchange of status for the gift of a research article was, and never is that simple. The bundle of responsibilities in this exchange includes (not exclusively) assurances of research integrity, access to data (optimally), and continuing conversations about the research results. The community gets to demand what it needs to realize the value of this gift for science.
Demand sharing is focused on a relationship between individuals and the group. Whereas a gift economy can be focused on how particular transactions are handled between individuals across their lifetimes, demand sharing is grounded on belonging to a group and knowing when and how to offer and to ask for goods from the group. You could say this is a certain form of gift economy, with added group-sanctioned cultural practices. Social distancing during a pandemic is a type of demand sharing. In this case, the group benefits when each individual participates, and the individual benefits when the whole group acts in concert.
Demand sharing resembles “tolerated scrounging” (Widlok 2013). There is no score to keep, as in monitored reciprocity, and no specific value attached to the goods, as in a market. In place of these are cultural practices and norms that work to preserve the process of sharing, guarantee sharing to all individual members, and protect the integrity of the shared resource pool through active governance. This is precisely what “commoning” in the academy supports.
Demand sharing practices require active cultural intention to remain clear and durable. You cannot put demand sharing on autopilot. Rules are less useful here than strategies (See: Making statements about open science). One non-hunter-gatherer example of demand sharing is what is called “expedition behavior.” “Expedition behavior involves putting the group’s goals and mission first, and showing the same amount of concern for others as you do for yourself. Jeff Ashby, a NASA space shuttle commander who has flown more than four hundred orbits around Earth, says that ‘expedition behavior — being selfless, generous, and putting the team ahead of yourself—is what helps us succeed in space more than anything else.’“ (Grant 2011). Expedition behavior also demands that the group leave no expedition member behind.
Demand sharing begins with a recognition of the legitimate demands from others. It is other-focused. Instead of serial, disengaged market transactions that have no consequent advantage for the group, demand sharing requires and rewards engagement with others. Consideration of others, and consequent consideration by others, creates social closeness: it is a holding close of others into a sharing society.
Demand sharing has been “operationalized” in smaller societies for millennia. Demand sharing practices are local and as complex as their locale requires. “…sharing is in itself a complex phenomenon, more complex than usually imagined by those who are not participating in the economy of sharing on a daily basis” (Widlok 2016). Responding to the specific demands of research arenas, science also groups its activities into smaller societies of researchers that share their own province of infinite play—their own precinct of phenomena, theories, and methods. Within and among these groups, demand sharing practices will become as complex as required to fulfill the needs of the group to discover, access, and mine their shared resources.
“A basic goal of provisioning is to reintegrate economic behaviors with the rest of one’s life, including social well-being, ecological relationships, and ethical concerns” (Helfrich and Bollier 2019).
The main kind of “demands” in a demand-sharing academy are demands that new research be shared with colleagues in a manner that promotes rapid reuse and further knowledge generation. You can consider these as “investment demands.” These demands provide a valuable return for each individual scholar and team, which only need to add their work into a shared repository in order to get culturally-supported access to the entire corpus. You add your “carrot” (or onion, or whatever) to the shared research soup bowl, and you get a whole meal back. Only this bowl is never empty, as its ingredients are digital and anti-rivalrous. So, you get a shared abundance of meals. These are “provisioning demands.” You get your fill of the latest data and research findings from across the planet.
A second group of demands center around science play (See: Open Science and infinite play). Within a culture of demand sharing, scientists and teams can demand that their institutions support science across its horizons, and through time within and beyond the lives of individual scientists. This means reaffirming those freedoms that allow science to advance at its own pace and without external influence, and provisioning science teaching and research as a public good (Newfield 2016). These new demands might include a durable, guaranteed minimum income for all researchers, say, and more university funds for new projects and science infrastructure. Freed from the enormous friction of self-interested finite games where stealing ideas and the fear of “getting scooped” guide a lack of sharing (Hyde 2009), the academy can focus on stewarding its resources and mining new knowledge from these.
The third group of demands are governance and stewardship responsibilities and activities that require individuals as commoners to work to maintain pooled resources and effective governance strategies across time. This governance “overhead” is inherently problematic when the pooled resources are open to all to use. One solution to this problem is to localize the resources (Neylon 2017) and task those who use them a lot to step up and be more active in their stewardship. This is one functional reason why scholarly commons (plural) will need to be localized for governance, and globalized for impact. The immediate issue this solution creates is the need for robust interoperability among the commons, including some sharing of cultural norms for mutual use of combined resources.
The last demands are really the first ones in the careers of scientists: the demands that students make on their teachers and schools to provision their learning path. If “tolerated scrounging” describes how scientists gather their research goods, teaching the next generation of scroungers means more than opening up scientific content access and understanding. Open-science teaching includes inculcating cultural knowhow about the norms and practices of commoning in scholarly commons.
“After giving talks about open science I’ve sometimes been approached by skeptics who say, ‘Why would I help out my competitors by sharing ideas and data on these new websites? Isn’t that just inviting other people to steal my data, or to scoop me? Only someone naive could think this will ever be widespread.’ As things currently stand, there’s a lot of truth to this point of view. But it’s also important to understand its limits. What these skeptics forget is that they already freely share their ideas and discoveries, whenever they publish papers describing their own scientific work. They’re so stuck inside the citation-measurement-reward system for papers that they view it as a natural law, and forget that it’s socially constructed. It’s an agreement. And because it’s a social agreement, that agreement can be changed. All that’s needed for open science to succeed is for the sharing of scientific knowledge in new media to carry the same kind of cachet that papers do today” (Nielson 2011).
[T]he work of culture more generally may be seen as training towards letting (things) go. If culture is all about conveying things and skills to others…then learning to let go of things that others appropriately demand is a permanent process. Just as those from whom I have received skills and knowledge (and positions and objects and my life) had to let go of their possessions in the course of their lives, so will I have to learn to let go…” (Widlok 2016).
In this Handbook, there is a lot of description of the future, open academy within a gift economy. If this sounds like an open scientist needs to spend their career giving away their knowledge, that’s actually pretty much spot on. But the other, equal, side to this is that an open scientist also gets to get what they need to do their research and build their life. The practice of getting-to-get as a feature of open science culture needs to be explored. What is clear is that this “half” of the gift economy in an abundant open academy is by far the bigger half. It’s like putting your potato in the common pot and getting a feast in return. Think of this gift economy as a loan-and-borrow economy, instead of a give-and-take economy. When you share, you also get to keep what you share, and when you borrow, you have no exclusive claim on what you’ve get: just a promise that there is more out there to use. Below, we will discover how this works.
“Saul Bellow, writing to a friend … said: ‘The name of the game is Give All. You are welcome to all my facts. You know them, I give them to you. If you have the strength to pick them up, take them with my blessing’” (Lethem 2007; Accessed July 20, 2020).
In his book Steal like an Artist, Auston Kleon (2012) reminds artists that their lives have been surrounded by art, and that their “original” ideas have been informed in myriad ways by their exposure to this. Stealing is unavoidable, so do it right. Additionally, new art (including music) is always positioned inside of and/or away from the art preceding this. There is an abundance of influences to use, and a debt to all of them. Artists need to be bold and remix what they find, to celebrate the old ideas in their new work. And like science, an artist borrows from the best in order to improve on this using their creative imaginations.
Today, within the academy, stealing practices—the hoarding, scooping, credit-grabbing kinds that are supported by the invented scarcity of ideas and the diminished value for generosity in science—flourish in the absence of social attention and alternative cultural norms. Tomorrow, when open science defines the norms for borrowing, sharing, and celebrated reuse, stealing can be banished to the social margins, and ridiculed as needed.
Borrowing is the main form of sharing in the academy’s gift economy. Investigate the meanings and potentials of what you find, and then transform these from those insights born of your personal onlyness (See: The Onlyness of the Career Open Scientist). Science is very much like an art here, with a similar relationship to its ideas, but a greater need to maintain the provenance of its knowledge goods. Everything in your science life is borrowed: the knowledge, the methods, every insight up to the point when you add your own, the data you collect. So your job is to learn how to borrow as a scientist.
You are a scientist. You’re not agent 007. You are really more like agent C20H25N3O. But you do have a license. A license to borrow. Come closer. Be honest. You are always on the lookout for ideas worth borrowing. If the journal article you’re reading is not worth borrowing, toss it away and keep looking. You are always looking. It’s called “research.” You hope your own team’s ideas are worth borrowing. You make borrowing these easy. It’s called “publication.” You are a professional thief. You keep careful track of the ideas you borrow. You know where they are from. You’ve read the articles, you’ve read the articles they cited. You’ve read the articles from the citations in those articles. Life would be a lot easier if you could just spin up new ideas on your own. It doesn’t work that way.
Borrowing as a scientist in the open-science economy means you get to ask for and take what you need, in culturally specific ways. You take resources to use and reuse, to mine and remix. You pull knowledge from these, and add insights to them in the process. In hunter-gatherer societies (and sometimes in college dormitories), this is called “tolerated scrounging.” In the academy it’s more like “celebrated reuse.” Open-science research repositories make reuse quick and easy, and they are filled with ideas worth borrowing. And, since these are “non-rivalrous” (See: Neylon 2016), an unlimited number of scientists can borrow them. Better still, the more these ideas are borrowed, the greater their value.
The culturally specific rules for borrowing are being fashioned through the governance processes of scholarly commons (scholarly commons), as these are created to steward common pooled resources toward optimal use. The removal of patents for basic research (See: Hyde 2009; Barnett 2020), is one starting point. Fully public open-access publishing is another. Start somewhere and grow a culture of tolerated scrounging for the resources in your scholarly commons.
“We may consider sharing to be tolerated scrounging but for the scrounging to be tolerated it has to build on a number of recognized modes of action and interaction” (Widlok 2013).
[R]esearchers saw maintaining responsible conduct as the mandatory responsibility of every individual scientist. By choosing this card, the discussants assumed that science’s most important responsibility to society was to produce reliable knowledge. Research misconduct is then seen as the main threat to this practice…” (Sigl et al 2020).
When you gift (publish) a new scholarly work, you shoulder every responsibility for the rigor in your methods and any issues with your data. This is the first of several social responsibilities (such as mentoring others) you always carry, and one of the keystone virtues the academy has demanded for hundreds of years. Still, you are not the first nor the final author of your own findings. That authority is attached to a thousand places in the prior ideas of others, and in the work of more scientists yet to happen. You merely added one piece to an ongoing solution to the puzzle of nature (or society, etc.): to the “one long experiment” (Martin 1998) that is science. Time to get humble; but if intellectual humility doesn’t sound like you, you can claim “hypo-egoic nonentitlement” (Banker and Leary 2019) instead.
Borrowing like a scientist in an open gift economy also means everyone else gets to borrow from you. When they borrow like scientists, this makes you happy. It means your works are borrow-worthy. You celebrate their reuse. In fact you need others to reuse your work to show its reproducibility. Your claim is that anyone would necessarily arrive at the very same insight you had, proving that this insight has a durable purchase on its object. If nobody can or does reuse your work, its value is unknown and even suspect.
What is harder to admit is the amount of luck, the confluence of good fortune that brought you to the event where you and your team acquired some new insight (Pluchino A. et al. 2018). Nobody gets to own serendipity. “Serendipity is a category used to describe discoveries that occur at the intersection of chance and wisdom” (Copeland 2019). Riding on the back of the serendipity of reading what you did, talking with whom you have, and trying something new, you’ve exercised rigor and wonder and perseverance enough through your research to find that one distinct piece of the puzzle to apply it exactly where it fits. Now, you are expected to honor and celebrate the many contemporary and prior ideas that helped you and your team arrive at the singular event within which this new insight was born (See: Shaming the giant). By this, you also show that you belong to the elite club of science. And those who borrow your ideas will honor and celebrate them in theirs.
As an open scientist, you have five jobs:
1. produce ideas worth borrowing, and;
2. make these ideas as easy to borrow as possible;
3. borrow as much from other scientists as you need, but borrow like a scientist;
4. become an active maintainer in your commons, to keep the borrowing opportunities rich and rewarding for everyone.
5. as a member of a scholarly commons, you also have the duty to create normative cultural practices to optimize borrowing going forward.
Your list of “good getting” practices will be fashioned to meet the needs of all the commoners in your community. Here’s a sample list:
Getting practices involve care and attention to the provenance of what’s being borrowed, and active credit for those who have made borrowing possible. Stealing practices all point to a game of personal gain based on hiding the sources of your own learning. Getting as a scientist aims to steward the abundance of open resources is a long-term—longer than any lifetime—practice.
“Disinterestedness: Scientists are motivated by the desire for knowledge and discovery, and not by the possibility of personal gain.
Self-Interestedness: Scientists compete with others in the same field for funding and recognition of their achievements” (Anderson, et al. 2007).
Let’s dig a little deeper into “celebrated reuse” and the history of science. The Mertonian norms of science include a notion of “disinterestedness.” At the time Merton was writing, this norm announced a basic freedom to pursue science without conflicts of interests, to shield basic science research from the motivations and (perverse) incentives that come with the marketplace, say, or with other external social/political/military desires. As Vannevar Bush (Accessed August 1, 2020) noted: “Scientific progress on a broad front results from the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown.” Disinterestedness is also the culturally valued attitude of “letting go” when others build on your findings.
Disinterestedness was, and still is, the classic norm that frees you to let others in the academy club borrow your work. The same lack of self interest that validates your independent research choice also validates you being able to let other people freely use your work. Since you chose to not let external interests determine your research path, you have no reason to hoard the results.
Disinterestedness is one of the social costs of academic freedom (you probably can’t have one without the other). It is the reason why the imbalance between responsibility (you have 100% of this) and authority (you have very little of this) makes perfect sense. You take the freedom to choose your research path in exchange for gifting the results back to the community; you release your personal interest in these results to benefit the whole scientific club.
If self-interest is your main incentive to do science, you are not doing open-science. Worse than that, you are doing science wrong. If you decide to wait until you have tenure to throw off self-interest (Anderson et al 2010), you are also doing it wrong. Certainly, we all have a stake in our own interests. Science expects us to care for these interests outside of our scientific explorations, and we need institutional reform and support to get there. But mainly, disinterestedness tells us to avoid conflicts with interests from outside the “republic of science” (Polanyi 1962).
“[M]uch of academic thinking brackets issues of emotions and values outside of academic understanding, even though emotions and values inhabit research and teaching by virtue of what we know, what we choose not to know, what we prioritise and what we trivialise” (Lynch and Ivancheva 2016).
Research needs to be free to follow its own objects, but being passionate about your research is no free ticket to act poorly with others (See: Six rules about passion in the workplace). Not caring about the marketplace and not caring for your colleagues are two different practices.
Disinterestedness is not an alibi to ignore/resist other organizational cultural values for the academy, values that include kindness and care in academy workplaces and in relations with colleagues. You can start by bracketing out the perverse marketplace incentives that might warp your research path and diminish your own passion for the pursuit of science. Passion is another part of science that is not peculiar to you. You are not the only person in the room or on your team that has been infected with the intellectual disease of science. This is a long-term global knowledge pandemic. Everyone gets to be infected—to be passionate—in their own way. Exploring these passions through years of rigorous research effort builds a kind of shared practical wisdom inside the profession.
The practical wisdom that underpins actually doing science removes the need for other incentives. The answer to the question: “How do you incentivize scientists to do research and teaching?” is simply this: “give them more opportunities to learn the practical wisdom required to do science” (See: The practical wisdom of science praxis). Science requires/rewards its own unique practical wisdom. In addition to the practical wisdom one might (and perhaps should) acquire through social experiences with others (colleagues, family, strangers), doing science offers opportunities to acquire practical wisdom through a career experiencing nature as a complex emergent system.
For many years, you borrowed learning from your teachers. Now, you encourage your students to scrounge new knowledge. Today, you borrow like a scientist: information from your objects of study and insights from conversations with your colleagues. In tomorrow’s open-science culture, culturally-informed practices for getting-to-get will help you and your team and your organization optimize the use of the emergent scholarly commons infrastructure and content. The work needed to articulate and support these practices will be significant. But know that the work needed to support stealing in the academy today is just as arduous, except that so many academics have already learned how. Unlearning these toxic cultural practices will take time and reflection.
Today, dozens of open-science platforms and communities are encouraging effective reuse. Reuse is one metric that deserves to become a goal (and one goal that makes a handy metric). How does your organization, your discipline, or your team celebrate active reuse? Where can it improve?
Unleash the “power of pull” for your science research
“In a closed society where everybody’s guilty, the only crime is getting caught. In a world of thieves, the only final sin is stupidity” (Thompson 1971).
“Pull allows each of us to find and access people and resources when we need them, while attracting to us the people and resources that are relevant and valuable, even if we were not even aware before that they existed” (Hagel 2010; Accessed February 26, 2020).
Why is Demand Sharing so important to open scientists like you? We are going to explore this question here. Let’s begin with the poster-child for research-sharing-gone-wrong: “for-profit science publishing.” At the same time you’ve been perfecting your demand-sharing techniques in the classroom, you’ve surrendered your research to one of the strangest marketplace transactions in modern times.
Academics give their research to publishers; give the publishers their copyrights; and also donate an additional sixty-eight million hours a year (Nature News Sept 7, 2018: <https://www.nature.com/articles/d41586-018-06602-y>) reviewing the work of others for free. Academic libraries must each pony up millions of dollars a year to keep their subscriptions current. The public gets dinged thirty to forty dollars (US) a pop just to read a single article. The process of selecting articles often leads to months or years between discovery and publication, and warps the output toward positive (and false-positive) “sexy science” results. The remainder of research results go unpublished. “Economists may not have terms adequate to describe a market as dysfunctional as the one operating for academic publishing” Neff (2020; Accessed February 26, 2020) notes.
Potts (et al. 2017) points to a failure of the publishing capacity of academic societies to scale with the blossoming of science output after World War II:
“The wartime and post-war expansion of public research funding and consequent expansion and globalisation of research communities were soon exploited by an entrepreneur-led proliferation of increasingly specialised journals, following the lead of Robert Maxwell’s Pergamon Press (Buranyi 2017). The small society presses, struggling to cope with growing scale, were supported and then largely supplanted by the ‘Big 5’ commercial presses: Elsevier (which acquired Pergamon in 1991), Wiley, Springer, Taylor & Francis and Sage. These newly-empowered players brought an industrial approach to the publication and dissemination process, for the first time realising the benefits that these specialised capital and skills could provide by operating at a scale that was unprecedented to that date. The successful publishers grew (and consolidated to grow further) alongside a pre-Cambrian explosion and specialisation of journals to create the modern landscape in which the majority of journals is owned, controlled or at least produced by a handful of globalised companies.”
A committee at the National Academies of Sciences (2018) offers additional historical information:
“The 1990s brought a wave of consolidation among scientific publishers, as Netherlands-based Elsevier acquired Pergamon, leaving it in control of over 1,000 journals (Buranyi 2017 [ibid]). Further increases in subscription prices and the advent of “big deal” agreements between publishers and libraries followed in the late 1990s. Under these agreements, publishers agree to provide online access to a bundle of their journals, including all back issues, priced at a discount to the sum of the individual journal subscriptions (Bergstrom et al. 2014). Despite paying lower per journal prices, total outlays by libraries increased to the point where this has been called the “serials crisis” (Panitch and Michalak 2005[white paper is no longer online]). In 2015, Larivière et al. found that the five most prolific publishers, including Reed-Elsevier, Taylor & Francis, Wiley-Blackwell, Springer, and Sage, control over one-half of all the scientific journal market, and that the profit margins of these companies have been in the range of 25 to 40 percent in recent years (Larivière et al. 2015). According to one economist who studies the industry, this situation ‘demonstrates a lack of competitive pressure in this industry, leading to so high profit levels of the leading publishers that they have not yet felt a strong need to change the way they operate’ (Björk 2017a)”.
Both of these accounts point to older, established cultural practices based on demand sharing within the academy being disrupted and displaced by marketplace profit seeking. By the end of the Nineteenth Century, the academy had taken control of its own research sharing practice through the advent of hundreds of member-run professional societies — each with their own publishing effort. Within these societies, members freely gave up their research for review and publication. University presses added their capacity as well.
In demand sharing, a “demand” is a culturally-grounded request
As academic institutions, the societies and universities demanded research finding from their members, in much the same fashion that students can demand knowledge from their professor in the lecture hall. Sharing is both expected and normative. Merton (1973) noted that:
“The institutional conception of science as part of the public domain is linked with the imperative for communication of findings. Secrecy is the antithesis of this norm; full and open communication its enactment. The pressure for diffusion of results is reenforced by the institutional goal of advancing the boundaries of knowledge and by the incentive of recognition which is, of course, contingent upon publication.”
Societies provided both the means of building the shared, public, academic corpus, and the platform for recognition. Yet this individual recognition was also tempered with the larger sense that all knowledge is interlinked and historically accumulated. Merton (ibid) writes: “The communal character of science is further reflected in the recognition by scientists of their dependence upon a cultural heritage to which they lay no differential claims.”
Demand sharing on the open web
Open science efforts in the last twenty years have been centrally focused on refactoring the means of academic publication to take advantage of the opportunities provided by the internet, and to remove the foreign, marketplace, logic in order to reassert the “communal character” of science publishing, grounded in the logic of demand sharing (although they haven’t called it that). Unlinking the act of giving research results back to the science community — which has long been a community norm — from the more recent practice of giving away research results to the marketplace — to own from there forward — restores these results as internal “gifts” within a community guided by demand sharing. There is more. At the same time that open science releases the academy from its recent marketplace bondage (freeing up financial resources in the process), a new, networked marketplace for “ideas” in and out of the academy is also challenging the notion of organizational knowledge ownership, in favor of what Hagel (et al. 2012) calls the “power of pull.”
Large corporations, fledgling start ups, and, yes, even ivory tower universities can access an explosion of shared knowledge and lateral learning when they decide to pull information from global networks. “Institutions can significantly amplify the power of pull, making it far easier to connect with a broader range of people and resources and to learn faster from each other than we ever could in the absence of institutions. We must therefore reclaim our institutions — whether from the inside of existing ones or by creating a new generation of our own.” (ibid) Open science works to reclaim the academy as learning hubs that can pull information from academy commons resources across the planet.
Goldman and Gabriel (2005) observed that “innovation happens elsewhere”; that the crowd- and network effects of open communities could assemble more talent, a greater variety of knowledge, and effective collective intelligence(s) well beyond those that any company/university/lab could afford to assemble internally. Their arguments were informed by Bill Joy, a co-founder of Sun Microsystems, who wrote in the 1990s: “no matter who you are, most of the smartest people work for someone else” (Wikipedia). This is known in management theory as Joy’s law. And it holds ever more strongly for your university, your agency, or your laboratory.
Many corporate management experts point out that openly sharing ideas across corporations (Golden and Gabriel 2005; Leadbetter 2005 <https://www.ted.com/talks/charles_leadbeater_on_innovation?> Accessed April 21, 2019), and gathering ideas from customers and external sources (Bissola et al. 2017), will lead to better, faster corporate innovation. In fact, you can say, with some authority, that the future of innovation in the academy will require the logic of demand sharing.
The marketplace logic of intellectual property ownership and practice of demand sharing for knowledge are antithetical. They do not play well together. For-profit efforts to include “open practices” invariably lead to open-washing, and the final closure of collected resources as intellectual property (Neylon 2017). Open for them means “free to acquire” and mainly serves to lower their resource costs. Demand sharing is an older practice, older in the academy, and still older in the species, being a primary form of cultural practice over thousands of years. It privileges internal goods over the external goods and incentives of the market.
To understand this further, jump to (See: Gifting and Reciprocity), where you can explore how each act of demand sharing builds a social bond that can be used to stimulate other occasions of sharing. The academy also needs to break completely from seeking to own intellectual property inside individual organizations (Against Patents in the Academy) in favor of academy-wide ownership supporting a shared resource commons for intellectual property. Current work on the creation of “Civic Trusts” offers a productive way forward for the academy (See: The Civic Trust; Accessed February 26, 2020).